Welcome to CSCAR's treatment assignment system.

Background: CSCAR's sequential treatment assignment
system is intended to assist researchers who are conducting
trials in which subjects are assigned sequentially to treatment
groups. It aims to provide treatment assignments that are
balanced across the levels of one or more pre-treatment
covariates. Sequential assignment is useful whenever a complete
list of all research subjects is not available at the beginning
of a trial. It is especially effective when a study will enroll
a small or moderate number of subjects.

Methodology: This system implements an approach to
treatment assignment using minimization that was developed by
Pocock and Simon (Biometrics 31, 1975). The
minimization approach reduces covariate imbalances by utilizing
non-uniform assignment probabilities for the different treatment
groups, in order to reduce the level of imbalance following each
round of treatment assignment. Although the probabilities are
not uniform, the treatment assignments are still random, which
reduces the risk that a user can bias the results of the trial
by selectively enrolling patients.

Security: This system identifies users through their
Google account id. Users must be signed into their Google
account whenever using the system. This system runs on Google
AppEngine and the data are stored on Google's servers. You will
be given the option to store either complete data or aggregated
data for the subjects in your study. In the latter case, only
the frequency distribution of each covariate within each
treatment group is retained by the system.